ILANIT 2020

Biological demonstrations of fast 3D super-resolution microscopy and rapid bacterial detection by pupil plane modification

Onit Alalouf 1 Roee Amit 2 Noa Eden 2 Boris Ferdman 4 Daniel Freedman 3,5 Sarah Goldberg 2 Racheli Gordon 1 Tomer Michaeli 3 Tal Naor 1 Elias Nehme 3 Reut Orange 4 Yael Shalev-Ezra 1 Lucien Weiss 1 Yoav Shechtman 1
1Technion, Department of Biomedical Engineering and Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering, Israel
2Technion, Department of Biotechnology and Food Engineering, Israel
3Technion, Department of Electrical Engineering, Israel
4Technion, Russel Berrie Nanotechnology Intitute,, Israel
5Haifa, Google Research, Israel

Biological processes in cells span 3 spatial dimensions. Fluorescence microscopy techniques such as confocal microscopy scan the entire volume of the object to visualize these processes and may lose important information due to slow acquisition times. We use Point Spread Function (PSF) engineering to modify the pupil plane of the microscope and to encode the Z position of the emitter in its image shape, allowing fast, 3D localization using a widefield microscope. Here, we demonstrate our PSF engineering advances in four biological applications: 1) Tracking chromosome reconfiguration during mating-type switching in live Saccharomyces Cerevisiae cells by simultaneous detection of fluorescently labeled DNA loci using our phase mask design for depth and color determination. We use existing as well as our own developed FROS (Fluorescent Repressor-Operator System) to label four different loci; 2) Following chromosomal compaction at the GAL locus in S. Cerevisiae using imaging flow cytometry with a modified emission optical path for high throughput 3D localization microscopy; 3) optimizing 3D single molecule localizations of mitochondria in fixed COS7 cells by deep learning; and 4) localizing telomeres in fixed U2OS cells with phase mask designed by deep learning for dense emitter samples.

Additionally, we use the pupil plane fluorescence pattern for the detection of early stages of bacterial growth, by following changes proportional to the refractive index of the sample. Our next step is to develop methods using this cost effective and ultrasensitive refractometry to detect bacterial resistance to antibiotics, and bacterial growth even before cell division.









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